Abstract
In this paper we report an ongoing work on an algorithm called DMEA (Evolutionary Algorithm based on the Differential Mutation). This algorithm is composed of differential mutation coupled with the “traditional” Gaussian mutation, fitness proportionate selection and generational replacement. We experimentally show that the DMEA is capable to generate chromosomes in a way that their distribution fits to the contour lines of the fitness function. Performance of DMEA was evaluated on the CEC2005 benchmark. Quality of results is comparable to many leading global optimization methods, including those which are based on the Differential Evolution paradigm.
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